dsp.MovingMinimum
R2026bMoving minimum
Description
The dsp.MovingMinimum
System object™ determines the moving minimum of the input signal along each channel,
independently over time. The object uses the sliding window method to determine the moving
minimum. In this method, a window of specified length is moved over each channel, sample by
sample, and the object determines the minimum of the data in the window.
You can make the window length tunable by setting
the EnableTunableWindowLength property to true. In
this mode, use the TunableWindowLength property to change the window
length even after you pass some data to the object and the object is locked. The
MaxWindowLength property specifies the maximum allowed window length.
For more details, see Algorithms. (since R2026b)
The dsp.MovingMinimum object and the movmin function both compute the moving minimum of the input signal. However,
the object can process large streams of real-time data and handle system states automatically.
The function performs one-time computations on data that is readily available and cannot
handle system states. For a comparison between the two, see System Objects vs MATLAB Functions.
To determine the moving minimum of the input:
Create the
dsp.MovingMinimumobject and set its properties.Call the object with arguments, as if it were a function.
To learn more about how System objects work, see What Are System Objects?
Creation
Syntax
Description
movMin = dsp.MovingMinimummovMin, using the default
properties.
movMin = dsp.MovingMinimum(Len)WindowLength property to Len.
movMin = dsp.MovingMinimum(PropertyName=Value)EnableTunableWindowLength to
true and to specify a maximum window length of 30, set
MaxWindowLength to 30.
Properties
Usage
Syntax
Description
Input Arguments
Output Arguments
Object Functions
To use an object function, specify the
System object as the first input argument. For
example, to release system resources of a System object named obj, use
this syntax:
release(obj)
Examples
Compute the moving minimum of a sum of three sine waves with varying amplitude. Use a sliding window of length 30.
Initialization
Set up an input signal that is a sum of three sine waves with frequencies at 2 Hz, 5 Hz, and 10 Hz. The sampling frequency is 100 Hz. Create a dsp.MovingMinimum object with a window length of 30.
sin = dsp.SineWave(SampleRate=100,... Frequency=[2 5 10],... SamplesPerFrame=100); movMin = dsp.MovingMinimum(30)
movMin =
dsp.MovingMinimum with properties:
SpecifyWindowLength: true
EnableTunableWindowLength: false
WindowLength: 30
Create a time scope for viewing the output.
scope = timescope(SampleRate=100,... TimeSpanSource="property",TimeSpan=10,... TimeSpanOverrunAction="Scroll",... ShowGrid=true,YLimits=[-4.5 4.5]);
Compute the Moving Minimum
Each sine wave component of the input signal has a different amplitude that varies with the iteration. Use the movMin object to determine the minimum value of the current sample and the past 29 samples of the input signal.
for index = 1:100 sin.Amplitude = rand(1,3); x = sum(sin(),2); xmin = movMin(x); scope([x,xmin]) end
Compute the moving minimum of a chirp signal and adapt the window length based on the instantaneous frequency. Use a longer window at low frequencies to capture the broad envelope. Use a shorter window at high frequencies to follow the rapid oscillations.
Create Chirp Signal
Create a dsp.Chirp object that sweeps from 1 Hz to 20 Hz. Set the sampling rate to 200 Hz and the frame size to 100 samples.
Fs = 200; frameSize = 100; numFrames = 20; f0 = 1; f1 = 20; chirp = dsp.Chirp(InitialFrequency=f0,... TargetFrequency=f1,... SampleRate=Fs,... SamplesPerFrame=frameSize)
chirp =
dsp.Chirp with properties:
Type: 'Linear'
SweepDirection: 'Unidirectional'
InitialFrequency: 1
TargetFrequency: 20
SweepTime: 1
InheritTargetTime: false
TargetTime: 1
InitialPhase: 0
SamplesPerFrame: 100
SampleRate: 200
OutputDataType: 'double'
Create Moving Minimum Object
Create a dsp.MovingMinimum object with tunable window length enabled. Set the maximum window length to 100 and enable auto-adjustment to handle edge cases.
movMin = dsp.MovingMinimum(EnableTunableWindowLength=true,... TunableWindowLength=100,... MaxWindowLength=100,... AutoAdjustInvalidWindowLength=true)
movMin =
dsp.MovingMinimum with properties:
SpecifyWindowLength: true
EnableTunableWindowLength: true
TunableWindowLength: 100
MaxWindowLength: 100
AutoAdjustInvalidWindowLength: true
Create a time scope to view the output.
scope = timescope(SampleRate=Fs,... TimeSpanSource="property",TimeSpan=numFrames*frameSize/Fs,... TimeSpanOverrunAction="Scroll",... ShowGrid=true,YLimits=[-2 2],... Title="Adaptive Moving Minimum of Chirp Signal");
Compute the Adaptive Moving Minimum
At each frame, estimate the instantaneous frequency and derive the window length from it. As the chirp frequency increases, reduce the window length to track the faster oscillations. Add noise to the chirp signal to simulate a realistic scenario.
for index = 1:numFrames x = chirp() + 0.2*randn(frameSize,1); instFreq = f0 + (f1 - f0) * index/numFrames; wl = round(100 * (1 - instFreq/f1) + 5); movMin.TunableWindowLength = wl; xmin = movMin(x); scope([x, xmin]) end
Algorithms
In the sliding window method, the output for each input sample is the minimum of the current sample and the Len−1 previous samples. Len is the length of the window in samples. When the algorithm computes the first Len−1 outputs, the length of the window is the length of the data that is available.
When you do not specify the window length, the algorithm chooses an infinite window length. In this mode, the output is the minimum of the current sample and all the previous samples in the channel.
Consider an example of computing the moving minimum of a streaming input data using the sliding window method. The algorithm uses a window length of 4. With each input sample that comes in, the window of length 4 moves along the data.
![Sliding window method for moving minimum with window length 4 and input samples [−1, −2, 3, 2, 5, 2]. At each time step n=0 through n=5, the window expands until length 4 is reached, then moves along the data. Moving minimum computes min for each window position, producing values −1, −2, −2, −2, −2, 2 at n=5](movmin_slidewin.png)
References
[1] Bodenham, Dean. “Adaptive Filtering and Change Detection for Streaming Data.” PH.D. Thesis. Imperial College, London, 2012.
Extended Capabilities
Version History
Introduced in R2016bSee Also
Functions
Objects
dsp.MovingMaximum|dsp.MovingAverage|dsp.MovingRMS|dsp.MovingStandardDeviation|dsp.MovingVariance|dsp.MedianFilter
